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Cytometric analysis of T cell phenotype using cytokine profiling for improved manufacturing of an EBV-specific T cell therapy.

Rachel S CooperAleksandra KowalczukGwen WilkieMark A VickersMarc L TurnerJohn D M CampbellAlasdair R Fraser
Published in: Clinical and experimental immunology (2021)
Adoptive immunotherapy using Epstein-Barr Virus (EBV)-specific T cells is a potentially curative treatment for patients with EBV-related malignancies where other clinical options have proved ineffective. We describe improved good manufacturing practice (GMP)-compliant culture and analysis processes for conventional lymphoblastoid cell line (LCL)-driven EBV-specific T cell manufacture, and describe an improved phenotyping approach for analysing T cell products. We optimized the current LCL-mediated clinical manufacture of EBV-specific T cells to establish an improved process using xenoprotein-free GMP-compliant reagents throughout, and compared resulting products with our previous banked T cell clinical therapy. We assessed effects of changes to LCL:T cell ratio in T cell expansion, and developed a robust flow cytometric marker panel covering T cell memory, activation, differentiation and intracellular cytokine release to characterize T cells more effectively. These data were analysed using a t-stochastic neighbour embedding (t-SNE) algorithm. The optimized GMP-compliant process resulted in reduced cell processing time and improved retention and expansion of central memory T cells. Multi-parameter flow cytometry determined the optimal protocol for LCL stimulation and expansion of T cells and demonstrated that cytokine profiling using interleukin (IL)-2, tumour necrosis factor (TNF)-α and interferon (IFN)-γ was able to determine the differentiation status of T cells throughout culture and in the final product. We show that fully GMP-compliant closed-process culture of LCL-mediated EBV-specific T cells is feasible, and profiling of T cells through cytokine expression gives improved characterization of start material, in-process culture conditions and final product. Visualization of the complex multi-parameter flow cytometric data can be simplified using t-SNE analysis.
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